Single-cell sequencing to quantify genomic integrity in cancer

Single-cell sequencing in pancreatic cancer research: A deeper understanding of heterogeneity and therapy

Pancreatic cancer, including pancreatic ductal adenocarcinomas (PDACs), is a malignant tumor with characteristics of tumor-stroma interactions. Patients often have a poor prognosis and a poor long-term survival rate. In recent years, rapidly-developing single-cell sequencing techniques have been used to analyze cell populations at a single-cell resolution, so that it is now possible to have a more in-depth and clearer understanding of the genetic composition of pancreatic cancer. In this review, we provide an overview of the current single-cell sequencing techniques and their applications in the exploration of intratumoral heterogeneity, the tumor microenvironment, therapy resistance, and novel treatments. Our hope is to provide new insight into the potential of precision therapy, which will perhaps one day lead to significant advances in PDAC treatment.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Extrachromosomal Circular DNA (eccDNA): From Chaos to Function

Extrachromosomal circular DNA (eccDNA) is a type of double-stranded circular DNA that is derived and free from chromosomes. It has a strong heterogeneity in sequence, length, and origin and has been identified in both normal and cancer cells. Although many studies suggested its potential roles in various physiological and pathological procedures including aging, telomere and rDNA maintenance, drug resistance, and tumorigenesis, the functional relevance of eccDNA remains to be elucidated. Recently, due to technological advancements, accumulated evidence highlighted that eccDNA plays an important role in cancers by regulating the expression of oncogenes, chromosome accessibility, genome replication, immune response, and cellular communications. Here, we review the features, biogenesis, physiological functions, potential functions in cancer, and research methods of eccDNAs with a focus on some open problems in the field and provide a perspective on how eccDNAs evolve specific functions out of the chaos in cells.

Tools used to assay genomic instability in cancers and cancer meiomitosis

Genomic instability is a defining characteristic of cancer and the analysis of DNA damage at the chromosome level is a crucial part of the study of carcinogenesis and genotoxicity. Chromosomal instability (CIN), the most common level of genomic instability in cancers, is defined as the rate of loss or gain of chromosomes through successive divisions. As such, DNA in cancer cells is highly unstable. However, the underlying mechanisms remain elusive. There is a debate as to whether instability succeeds transformation, or if it is a by-product of cancer, and therefore, studying potential molecular and cellular contributors of genomic instability is of high importance. Recent work has suggested an important role for ectopic expression of meiosis genes in driving genomic instability via a process called meiomitosis. Improving understanding of these mechanisms can contribute to the development of targeted therapies that exploit DNA damage and repair mechanisms. Here, we discuss a workflow of novel and established techniques used to assess chromosomal instability as well as the nature of genomic instability such as double strand breaks, micronuclei, and chromatin bridges. For each technique, we discuss their advantages and limitations in a lab setting. Lastly, we provide detailed protocols for the discussed techniques.

Single-cell sequencing technology in tumor research

Tumor heterogeneity is a key characteristic of malignant tumors and a significant obstacle in cancer treatment and research. Although bulk tissue sequencing has wide coverage and high accuracy, it can only represent the dominant cell signal information of each sample, while masking the unique gene expression of rare cells; therefore it cannot represent genes that are unstable within a subgroup, but unchanged in a majority of cells. With the progress of genomic technology, the emergence of single-cell sequencing (SCS) has effectively solved the above problem. Genetic, transcriptomic and epigenetic sequencing at the single-cell level provides an important basis for us to correctly classify the cell subsets of heterogeneous tumor populations and to reveal the process of complex changes in tumor cells at the molecular level. Single-cell sequencing technology has been applied to the field of cancer, revealing exciting discoveries in the potential mechanisms of tumor driver gene mutation, clonal evolution, invasion and metastasis. It also provides favorable conditions for developing new tumor biomarkers and providing more accurate and individualized targeted tumor therapy. Herein, we review the steps and methods of single-cell sequencing and highlight the application of SCS in tumor diagnosis and clinical treatment.

Research and application of single-cell sequencing in tumor heterogeneity and drug resistance of circulating tumor cells

Malignant tumor is a largely harmful disease worldwide. The cure rate of malignant tumors increases with the continuous discovery of anti-tumor drugs and the optimisation of chemotherapy options. However, drug resistance of tumor cells remains a massive obstacle in the treatment of anti-tumor drugs. The heterogeneity of malignant tumors makes studying it further difficult for us. In recent years, using single-cell sequencing technology to study and analyse circulating tumor cells can avoid the interference of tumor heterogeneity and provide a new perspective for us to understand tumor drug resistance.

Genome‑wide copy number analysis of circulating tumor cells in breast cancer patients with liver metastasis

The genome‑wide copy number analysis of circulating tumor cells (CTCs) provides a promising prognostic biomarker for survival in breast cancer liver metastasis (BCLM) patients. The present study aimed to confirm the prognostic value of the presence of CTCs in BCLM patients. We previously developed an assay for the genome‑wide pattern differences in copy number variations (CNVs) as an adjunct test for the routine imaging and histopathologic diagnosis methods to distinguish newly diagnosed liver metastases and recurrent liver metastases. Forty‑three breast cancer patients were selected for this study in which 23 newly diagnosed and 20 recurrent liver metastases were diagnosed by histopathology and 18F‑FDG PET/CT imaging. CTCs were counted from all patients using the CellSearch system and were confirmed by cytomorphology and three‑color immunocytochemistry. Genomic DNA of single CTCs was amplified using multiple annealing and looping based amplification cycles (MALBAC). Then, we compared the CTC numbers of newly diagnosed and recurrent BCLM patients using Illumina platforms. A high CTC frequency (>15 CTCs/7.5 ml blood) was found to be correlated with disease severity and metastatic progression, which suggests the value for CTCs in the diagnosis of BCLM in comparison with pathohistology and PET/CT imaging (P>0.05). Moreover, CTCs isolated from BCLM patients remained an independent prognostic detection factor associated with overall survival (P=0.0041). Comparison between newly diagnosed and recurrent liver metastases revealed different frequencies of CNVs (P>0.05). Notably, the CNV pattern of isolated CTCs of recurrent BCLM patients was similar to recurrent liver metastases (nearly 82% of the gain/loss regions). Functional enrichment analysis identified 25 genes as a CNV signature of BCLM. Among them, were defensin and β‑defensin genes, which are significantly associated with anti‑angiogenesis and immunomodulation signaling pathways. High CTC frequencies are effective in the evaluation and differentiation between newly diagnosed liver metastases from recurrent liver metastases. Future clinical studies will be necessary to fully determine the prognostic potential of CTC cluster signatures in patients with BCLM.

Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

Effective cancer treatment has been precluded by the presence of various forms of intratumoral complexity that drive treatment resistance and metastasis. Recent single-cell sequencing technologies are significantly facilitating the characterization of tumor internal architecture during disease progression. New applications and advances occurring at a fast pace predict an imminent broad application of these technologies in many research areas. As occurred with next-generation sequencing (NGS) technologies, once applied to clinical samples across tumor types, single-cell sequencing technologies could trigger an exponential increase in knowledge of the molecular pathways involved in cancer progression and contribute to the improvement of cancer treatment.

Clonal Evolution and Changes in Two AML Patients Detected with A Novel Single-Cell DNA Sequencing Platform

Next-generation sequencing (NGS) is used to detect gene variants in genetically complex cell populations of cancer patient samples. Traditional bulk analysis can only provide average variant allele frequencies of the targeted genes across all sampled cells. It fails to resolve mutational co-occurrences and may miss rare cancer cells. Genome analysis at the single cell level offers the opportunity to more fully resolve clonal architecture. Peripheral blood mononuclear cells were sampled from acute myeloid leukemia patients longitudinally and single-cell DNA sequencing libraries were generated with a novel droplet-based microfluidics approach. Molecular profiling of single nucleotide variants across thousands of cells revealed genetic chimerism in patients after bone marrow transplantation (BMT). Importantly, hierarchical clustering analysis of single nucleotide variants (SNVs) uncovered a distinct oncogenic clone of cells carrying mutated tumor-suppressor and/or oncogene(s). This novel single-cell DNA sequencing approach enabled precise monitoring of engraftment and revealed clonal evolution of oncogenic cells during the progression and treatment of the disease.

Moonshot Objectives: Catalyze New Scientific Breakthroughs-Proteogenomics

Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their modifications-and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with the Cancer Moonshot, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic, and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.